annotate _FullBNT/KPMtools/mk_stochastic.m @ 9:4ea6619cb3f5 tip

removed log files
author matthiasm
date Fri, 11 Apr 2014 15:55:11 +0100
parents b5b38998ef3b
children
rev   line source
matthiasm@8 1 function [T,Z] = mk_stochastic(T)
matthiasm@8 2 % MK_STOCHASTIC Ensure the argument is a stochastic matrix, i.e., the sum over the last dimension is 1.
matthiasm@8 3 % [T,Z] = mk_stochastic(T)
matthiasm@8 4 %
matthiasm@8 5 % If T is a vector, it will sum to 1.
matthiasm@8 6 % If T is a matrix, each row will sum to 1.
matthiasm@8 7 % If T is a 3D array, then sum_k T(i,j,k) = 1 for all i,j.
matthiasm@8 8
matthiasm@8 9 % Set zeros to 1 before dividing
matthiasm@8 10 % This is valid since S(j) = 0 iff T(i,j) = 0 for all j
matthiasm@8 11
matthiasm@8 12 if (ndims(T)==2) & (size(T,1)==1 | size(T,2)==1) % isvector
matthiasm@8 13 [T,Z] = normalise(T);
matthiasm@8 14 elseif ndims(T)==2 % matrix
matthiasm@8 15 Z = sum(T,2);
matthiasm@8 16 S = Z + (Z==0);
matthiasm@8 17 norm = repmat(S, 1, size(T,2));
matthiasm@8 18 T = T ./ norm;
matthiasm@8 19 else % multi-dimensional array
matthiasm@8 20 ns = size(T);
matthiasm@8 21 T = reshape(T, prod(ns(1:end-1)), ns(end));
matthiasm@8 22 Z = sum(T,2);
matthiasm@8 23 S = Z + (Z==0);
matthiasm@8 24 norm = repmat(S, 1, ns(end));
matthiasm@8 25 T = T ./ norm;
matthiasm@8 26 T = reshape(T, ns);
matthiasm@8 27 end